4 papers
On Predicting Vulnerability Severity Using In-Context Learning: An Industrial Case Study
Daniel Rodriguez-Cardenas, David Nader Palacio, Anna Schmedding +8
Modern software systems require earlier and more scalable vulnerability severity assessment to reduce exposure to high-impact security flaws. Security analysts typically assign CVS…
Beyond Pixels: Introspective and Interactive Grounding for Visualization Agents
Yiyang Lu, Woong Shin, Ahmad Maroof Karimi +3
Vision-Language Models (VLMs) frequently misread values, hallucinate details, and confuse overlapping elements in charts. Current approaches rely solely on pixel interpretation, cr…
Safety Interventions against Adversarial Patches in an Open-Source Driver Assistance System
Cheng Chen, Grant Xiao, Daehyun Lee +4
Drivers are becoming increasingly reliant on advanced driver assistance systems (ADAS) as autonomous driving technology becomes more popular and developed with advanced safety feat…
Black-box Adversarial Attacks on CNN-based SLAM Algorithms
Maria Rafaela Gkeka, Bowen Sun, Evgenia Smirni +3
Continuous advancements in deep learning have led to significant progress in feature detection, resulting in enhanced accuracy in tasks like Simultaneous Localization and Mapping (…